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Voice recognition technology using neural networks
Joint Authors
Zaatri, Abd al-Wahhab
Azzizi, Norelhouda
al-Azhar, Fuad Rahmani
Source
Journal of New Technology and Materials
Issue
Vol. 5, Issue 1 (30 Jun. 2015), pp.27-31, 5 p.
Publisher
Larbi Ben M'hidi Oum el-Bouaghi University
Publication Date
2015-06-30
Country of Publication
Algeria
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
This paper presents the use of a Multi-Layer Perceptron Neural Nets (MLP-NN) for voice recognition dedicated to generating robot commands.
Our main goal concerns the estimation of the minimal number of elements required for the learning process in order to ensure an acceptable success of the neural nets recognition system.
As the MLP requires references for the spoken words, we have provided these references by the means of a supervised classifier based on the mean square error.
An experimental approach has been followed for the design of experiments enabling to determine the minimal elements in the sample for each voice command.
Satisfactory results have been obtained leading to a better understanding of variability of the system functioning.
Finally, we have noticed that the success rate of the MLP and the minimal number of elements used for the learning process depend on the spoken word structure and of the variability of the situation (word length, noise, speaker, etc).
American Psychological Association (APA)
Zaatri, Abd al-Wahhab& Azzizi, Norelhouda& al-Azhar, Fuad Rahmani. 2015. Voice recognition technology using neural networks. Journal of New Technology and Materials،Vol. 5, no. 1, pp.27-31.
https://search.emarefa.net/detail/BIM-604893
Modern Language Association (MLA)
al-Azhar, Fuad Rahmani…[et al.]. Voice recognition technology using neural networks. Journal of New Technology and Materials Vol. 5, no. 1 (2015), pp.27-31.
https://search.emarefa.net/detail/BIM-604893
American Medical Association (AMA)
Zaatri, Abd al-Wahhab& Azzizi, Norelhouda& al-Azhar, Fuad Rahmani. Voice recognition technology using neural networks. Journal of New Technology and Materials. 2015. Vol. 5, no. 1, pp.27-31.
https://search.emarefa.net/detail/BIM-604893
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 31
Record ID
BIM-604893